期刊
STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS
卷 22, 期 4, 页码 -出版社
WALTER DE GRUYTER GMBH
DOI: 10.1515/snde-2016-0061
关键词
filtering; Laplace series expansion; nonlinear time series; regime switching model; smooth transition model
In this paper, we develop a new class of parametric nonlinear time series models by combining two important classes of models, namely smooth transition models and hidden Markov regime-switching models. The class of models is general and flexible enough to incorporate two types of switching behavior: smooth state transitions and abrupt changes in hidden states. The estimation of the hidden states and model parameters is performed by applying filtering theory and a filter-based expectation-maximization (EM) algorithm. Applications of the model are illustrated using simulated data and real financial data. Other potential applications are mentioned.
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